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. An assessment of climate change impacts at different levels of global warmingis crucial to inform the policy discussion about mitigation targets, as wellas for the economic evaluation of climate change impacts. Integratedassessment models often use global mean temperature change ( Δ GMT) as asole measure of climate change and, therefore, need to describe impacts as afunction of  Δ GMT. There is already a well-established framework forthe scalability of regional temperature and precipitation changeswith  Δ GMT. It is less clear to what extent more complex biological orphysiological impacts such as crop yield changes can also be described interms of  Δ GMT, even though such impacts may often be more directlyrelevant for human livelihoods than changes in the physical climate. Here weshow that crop yield projections can indeed be described in termsof  Δ GMT to a large extent, allowing for a fast estimation of cropyield changes for emissions scenarios not originally covered by climate andcrop model projections. We use an ensemble of global gridded crop modelsimulations for the four major staple crops to show that the scenariodependence is a minor component of the overall variance of projected yieldchanges at different levels of  Δ GMT. In contrast, the variance isdominated by the spread across crop models. Varying CO2 concentrations are shown to explain only a minor component of crop yieldvariability at different levels of global warming. In addition, we find thatthe variability in crop yields is expected to increase with increasingwarming in many world regions. We provide, for each crop model, geographicalpatterns of mean yield changes that allow for a simplified description ofyield changes under arbitrary pathways of global mean temperature and CO2 changes, without the need for additional climate and crop modelsimulations.

Changes in crop yields and their variability at different levels of global warming